Top Data & Analytics Jobs in San Luis Obispo, CA

Design, build, and own scalable data pipelines and warehousing architecture from ingestion through analytics and incentive payouts. Lead data platform architecture, dbt modeling, data quality, lineage, observability, performance, and cost management. Partner with engineers and analysts on telematics accuracy and driver incentive reporting. Use AI coding tools daily to develop and review pipelines, SQL, and data models.

Analyzes complex healthcare data to identify trends, develop statistical and machine learning methodologies, and produce actionable insights. Builds dashboards and reports, supports product and business decisions, promotes data literacy, and collaborates with cross-functional teams. The role also ensures analytics practices comply with healthcare privacy, governance, security, and regulatory requirements, including HIPAA.

Convert, map, load, validate, and troubleshoot banking data for client implementations on the Lumin Digital platform. The role manages data conversion projects through launch, collaborates with clients and cross-functional teams, resolves data and system issues, identifies project risks, and improves conversion processes. Responsibilities include testing multiple file formats, ensuring data integrity, supporting vendor transitions and mergers, generating exception reports, and providing technical consultation.

Design and manage financial systems for accurate cashback calculations, build and maintain reconciliation processes, ensure data integrity for yield-bearing instruments, collaborate with compliance, and partner with cross-functional teams to improve financial system efficiency.

Manages a data engineering team responsible for scalable, reliable data pipelines, infrastructure, and analytics tooling. Provides mentorship, performance management, and technical leadership while coordinating with product, analytics, finance, compliance, engineering, and regulators. Prioritizes cross-functional projects, supports data architecture and governance, ensures performance and reliability, and operates within strict regulatory and audit requirements.

Own the company’s data function by designing and optimizing Snowflake architecture, pipelines, integrations, data models, BI dashboards, metric definitions, governance, and data-quality standards. Partner with leadership and cross-functional teams to translate operational needs into trusted data products. Automate recurring reporting, troubleshoot ingestion issues, perform ad hoc analysis, and establish scalable analytics practices as the first dedicated analytics hire.

Owns enterprise workforce intelligence and employee listening strategy. Analyzes employee sentiment, workforce trends, talent, skills, organizational effectiveness, and work data to identify risks and opportunities. Develops dashboards, analytical methodologies, AI-enabled insight products, and self-service resources. Partners with HR leaders and data owners to translate complex quantitative and qualitative findings into actionable recommendations for workforce planning, succession, organization design, automation, and capability decisions.

Design, develop, and publish advanced interactive Power BI reports and dashboards; define data structures and ETL needs; build analytics models using Microsoft BI stack (Power BI, SSAS/AAS, dataflows); use DAX and SQL to implement complex logic; collaborate with data engineering and business partners; mentor junior developers and performance-tune reports.

Supports loyalty and retention analytics through A/B test management, KPI tracking, recurring dashboards, and performance reporting. Monitors churn, winback, cancellation, and loyalty metrics; identifies trends, risks, and opportunities; and translates findings into actionable recommendations. The role also manages loyalty merchandise planning and replenishment, collaborates with Data Science and program owners, coordinates analytics requests, and prepares MBR/QBR materials.

Own sales analytics and forecasting as the trusted source of truth for sales leadership. Build predictive and machine learning models to assess deal close likelihood and slippage, maintain Salesforce and Tableau dashboards, improve data governance, and translate complex business questions into actionable GTM recommendations. Partner with Sales, Marketing, and Finance on reporting standards, strategic planning, QBRs, and executive insights.